remove hybridize

tests/python/unittest/test_gluon_rnn.py

@@ -352,8 +352,6 @@ def check_rnn_layer_forward(layer, inputs, states=None, run_only=False):
     np_out = out.asnumpy()
     np_dx = inputs.grad.asnumpy()
 
-    layer.hybridize()
-
     with mx.autograd.record():
         if states is not None:
             out = layer(inputs, states)
@@ -402,7 +400,6 @@ def test_rnn_layers():
     net.add(gluon.nn.BatchNorm(axis=2))
     net.add(gluon.nn.Flatten())
     net.add(gluon.nn.Dense(3, activation='relu'))
-    net.hybridize()
     net.collect_params().initialize()
     with mx.autograd.record():
         net(mx.nd.ones((2, 3, 10))).backward()
@@ -412,7 +409,6 @@ def test_rnn_layers():
     net2.add(gluon.nn.BatchNorm(axis=2))
     net2.add(gluon.nn.Flatten())
     net2.add(gluon.nn.Dense(3, activation='relu'))
-    net2.hybridize()
     net2.collect_params().initialize()
     with mx.autograd.record():
         net2(mx.nd.ones((2, 3, 10))).backward()
@@ -502,7 +498,6 @@ def test_cell_fill_shape():
 @assert_raises_cudnn_disabled()
 def test_layer_fill_shape():
     layer = gluon.rnn.LSTM(10)
-    layer.hybridize()
     check_rnn_layer_forward(layer, mx.nd.ones((3, 2, 7)))
     print(layer)
     assert layer.l0_i2h_weight.shape[1] == 7, layer.l0_i2h_weight.shape[1]